Active image optimization for lattice light sheet microscopy in thick samples

Lattice light-sheet microscopy (LLSM) is a very efficient technique for high resolution 3D imaging of dynamic phenomena in living biological samples. However, LLSM imaging remains limited in depth due to optical aberrations caused by sample-based refractive index mismatch. Here, we propose a simple and low-cost active image optimization (AIO) method to recover high resolution imaging inside thick biological samples. AIO is based on (1) a light-sheet autofocus step (AF) followed by (2) an adaptive optics image-based optimization. We determine the optimum AIO parameters to provide a fast, precise and robust aberration correction on biological samples. Finally, we demonstrate the performances of our approach on sub-micrometric structures in brain slices and plant roots.

Automated summary

Lattice light-sheet microscopy (LLSM) is an efficient technique for high resolution 3D imaging of dynamic phenomena in biological samples. However, optical aberrations caused by refractive index mismatch limit the depth of LLSM imaging. To address this issue, we propose a simple and low-cost active image optimization (AIO) method to recover high resolution imaging in thick biological samples.